Neuron1c/mcp-notebooks
If you are the rightful owner of mcp-notebooks and would like to certify it and/or have it hosted online, please leave a comment on the right or send an email to henry@mcphub.com.
mcp-notebooks is a server designed for executing notebook code in a controlled environment, allowing for progressive code execution and error handling.
mcp-notebooks
Notebook execution MCP server
Pretty dangerous to use in its current state
Rationale
Why not just execute code with literally any other already existing python execution server. This MCP server allows your LLM to progressively execute code and react to mistakes faster in a sort of EDA fashion. Variables are retained in the kernel and can be used in future executions.
Claude install
Okay listen buddy, it's not a one line process and run some node something. This really really should be run in a docker environment to protect your system from the AI overlor... I mean Claude. So go install docker and come back
Welcome back. This is not on DockerHub yet so run the following commands:
git clone git@github.com:Neuron1c/mcp-notebooks.git
cd mcp-notebooks
docker build . -t mcp-notebooks:latest
Halfway there, add the following to your claude_desktop_config.json
StdIO
{
"mcpServers": {
"notebooks": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"mcp-notebooks:latest"
]
}
}
}
SSE
Or run it manually
docker run -p 3001:3001 mcp-notebooks:latest
And now the config.json
{
"mcpServers": {
"notebooks": {
"command": "npx",
"args": [
"supergateway",
"--sse",
"http://localhost:3001/sse"
]
}
}
}
Add Python Libraries
As it stands the project dependencies are scoped to the bare minimum of what's needed to run the server. To add more you need to install poetry, after you have fought with that (protip use pipx)
uv add your-package
recommended packages to add
- numpy
- pandas
- scikit-learn
- matplotlib
- seaborn
I've found the AI really tries to use the graphing packages when demonstrating things to your
TODO
- View notebooks
- Sandbox the environment more
- Scheme a data ingestion scenario (Kedro catalog?)
- Dependency injection (Or just let the user pull and build their own container)
